CN109033452A - A kind of data warehouse is intelligent to construct stowage and system - Google Patents
A kind of data warehouse is intelligent to construct stowage and system Download PDFInfo
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Abstract
The present invention relates to data warehouses to construct management system technical field, intelligently building stowage and a kind of data warehouse intelligently construct Load System to specially a kind of data warehouse, the system includes mode input module, and the mode input module is used to input Data Vault model for user and defines file and generate Data Vault model；Model names module, and model name module is used for the Naming conventions according to Data Vault model, output library, table, field title；Table module is built, the table module of building is for generating the initialization statement of corresponding library and table according to the title in the library of Data Vault model and model name module output, table and field, and this method is based on system above realization.Intelligently building Load System, realization data pick-up, data mart modeling and the task schedule that can be automated reduce the workload of exploitation and maintenance to a kind of data warehouse provided by the invention, improve the efficiency of Data Warehouse for Enterprises building and maintenance.
Description
Technical field
The present invention relates to data warehouses to construct management system technical field, and intelligently building loads specially a kind of data warehouse
Method and system.
Background technique
Data Vault model be towards details, traceable history, combine third normal form and Star Model advantage
A new generation data warehouse model.The foundation and maintenance of global data warehouse based on Data vault model are one multiple
Miscellaneous engineering, developed comprising Data vault modeling, data warehouse initialization, the exploitation of data pick-up task, data mart modeling task,
All multitasks such as task schedule exploitation.The development cycle that the prior art needs to grow very much, and it is related to Data Analyst, data mining
The professional technician of all polymorphic types such as engineer, control engineer needs a large amount of duplicate when service logic changes
Development.
Patent CN201510272096.1 discloses a kind of table logical relation based on original service library, automatically generated data
The automated construction method and device of the initialization of the Data vault model and completion data warehouse in warehouse, shortcoming exist
Very complicated in service logic relationship, table logical relation is difficult to be completely covered；And based on the reason of the aspect of performance, ring is produced
Border database does not establish external key and the constraint relationship generally, and the incidence relation between table is difficult directly to take.Importantly, should
The automation for all multi-steps such as in method and subsequent data pick-up, data mart modeling, task schedule is not implemented, and these links account for
The most of workload of data warehouse exploitation and maintenance.
Summary of the invention
The invention is intended to provide, a kind of data warehouse is intelligent to construct stowage and system, the realization data that can be automated
Extraction, data mart modeling and task schedule, the workload of reduction exploitation and maintenance improve what Data Warehouse for Enterprises was constructed and safeguarded
Efficiency.
In order to solve the above-mentioned technical problem, this patent provides the following technical solutions:
A kind of data warehouse intelligence building Load System, comprising:
Mode input module, the mode input module, which is used to input Data Vault model for user, defines file and life
At Data Vault model；
Model names module, and model name module is used for the Naming conventions according to Data Vault model, output library,
The title of table, field；
Build table module, it is described build table module for according to the library of Data Vault model and model name module output,
The title of table and field generates the initialization statement in corresponding library and table；
Data extraction module, for library, table and the word according to Data Vault model and model name module output
The title of section generates and exports the sentence of isolating for extracting data to data warehouse patch active layer from source database；
Data loading module, for library, table and the word according to Data Vault model and model name module output
The title of section is generated and is exported and data are pasted the loading language that active layer is loaded into the table for building the foundation of table module from data warehouse
Sentence；
Task analysis module, the task analysis module be used for isolate sentence and load sentence analyze, obtain
Task dependence data and resource time-consuming data；
Task scheduling modules, the task scheduling modules are used for according to task dependence data and resource time-consuming data pair
Isolate sentence and load sentence execution be scheduled.
In technical solution of the present invention, the definition text of the Data Vault model to be established is inputted by mode input module
Part, this definition file generally define some basic information of Data Vault model, such as each field information of standard scale,
The satellite informations such as renewal time, update personnel, then according to this definition file generated Data Vault model；Model names module
It is generated according to the Naming conventions of the Data Vault model specification and exports each library, table and word under the Data Vault model
The title of section builds table module and then generates the initialization statement for creating corresponding table and library according to the title of generation；Data pick-up mould
Block and data loading module generate isolate sentence and the loading sentence of data respectively；In the present solution, also setting up task analysis mould
Block sentence and loads sentence and analyzes to above-mentioned isolate, by task scheduling modules based on the analysis results to each language of isolating
Sentence and the execution sequence for loading sentence are scheduled with the time.Compared with prior art, the pumping of data is realized in the application
It takes, the processing of dynamicization of all multi-steps such as data mart modeling, task schedule, related personnel only needs to be concerned about the service logic of core i.e.
Can, it does not need concern and develops details too much, significantly reduce the development cycle of global data warehouse, reduce exploitation
Staff size and cost, improve global data warehouse exploitation and maintenance automation, intelligent level.
It further, further include metadata verification completion module, the metadata verification completion module is used for according to Data
The metadata that the field information and inquiry source database of Vault model obtain verifies the field of Data Vault model
And information completion.By metadata verification completion module according to the metadata fields information of actual source database to Data
The field of Vault model carries out verification and information completion, it is ensured that the unification of field.
It further, further include field data types adaptation module, the field data types adaptation module is used for Data
The data type of the field of the data type and metadatabase of the field of Vault model is adapted to.In source database and target
Type of database is not identical to ensure that field data format is mutually unified by this step.
Further, the data extraction module includes tool of isolating, and the data loading module includes data processing tools,
The task scheduling modules include scheduling tool, and the tool of isolating, output handling implement and scheduling tool are with plug-in unit
Form is present in corresponding module.These tools are present in corresponding module in the form of plug-in unit, this modularization is inserted
What the form of part can be convenient replaces these tools, is handled using other algorithms, convenient for expanding to system
And transformation, so that the versatility of system is stronger.
It further, further include configuration module, the configuration module is used to carry out database essential information and configuration item
Configuration.It is configured by configuration parameter etc. of the configuration module to the essential information such as link information, modules of database, side
Just system is modified and is regulated and controled.
The present invention also provides a kind of data warehouses intelligently to construct stowage, method includes the following steps:
Mode input step defines file generated Data Vault model according to input Data Vault model；
Completion step is verified, the metadata obtained according to the field information of Data Vault model and inquiry source database
Verification and information completion are carried out to the field of Data Vault model；
Model names step, according to the Naming conventions of Data Vault model, export library, table, field title；
Table step is built, according to the Data Vault model and model name module after metadata verification completion module completion
The title in the library of output, table and field generates the initialization statement of corresponding library and table；
Data pick-up step, according to the library of Data Vault model and model name module output, table and field
Title generates and exports the sentence of isolating for extracting data to data warehouse patch active layer from source database；
Data loading step, according to the library of Data Vault model and model name module output, table and field
Title is generated and is exported and data are pasted the loading sentence that active layer is loaded into the table for building the foundation of table module from data warehouse；
Task analysis step, to isolate sentence and load sentence analyze, obtain task dependence data and money
Source time-consuming data；
Task schedule step, according to task dependence data and resource time-consuming data to sentence and the loading sentence of isolating
Execution be scheduled.
Further, it is verifying completion step and is building between table step further include: field data types adaptation step, by Data
The data type of the field of the data type and metadatabase of the field of Vault model is adapted to.
Detailed description of the invention
Fig. 1 is the logic diagram in a kind of data warehouse intelligence building Load System embodiment of the present invention.
Specific embodiment
It is further described below by specific embodiment:
As shown in Figure 1, the data warehouse of the present embodiment intelligently building Load System, including mode input module, model life
Name module, configuration module, field data types adaptation module, builds table module, data pick-up mould at metadata verification completion module
Block, data loading module, task analysis module and task scheduling modules, in which:
Mode input module is used to input Data Vault model for user and defines file and generate Data Vault model.
The file format that Data Vault model defines file includes but is not limited to structure or semi-structured file, as xml, csv,
Txt, json etc., the content that Data Vault model defines file includes but is not limited to Hub literary name segment information, Link literary name section letter
Breath, Sat literary name segment information, Pit literary name segment information, Bridge literary name segment information and renewal time update personnel, limitation item
The satellite informations such as part, dependence, Naming conventions, alias.
Model names module to be used for the Naming conventions according to Data Vault model, to be established in output data warehouse
Library, table, field title.
Configuration module is deposited in configuration module for configuring to the configuration item of database essential information and modules
Contain the link informations such as address, account, the password of essential information such as database of database.By configuration module to database
The configuration parameter etc. of essential information such as link information, modules is configured, convenient that system is modified and is regulated and controled.
Metadata verification completion module can according to the link information of database from data base querying metadata, and according to
The metadata that the field information of Data Vault model and inquiry source database obtain to the field of Data Vault model into
Row verification and information completion.
Specifically, metadata verification completion module includes data resolution module, comparison correction verification module and completion amendment mould
Block, data resolution module obtain field, comparison correction verification module is used for Data for parsing to metadata from metadata
The field of Vault model is compared and is verified in the field of acquisition, find out the field not having in Data Vault model and
The field having differences, completion correction module are used to select no field and the field having differences for user,
And the field of selection is subjected to completion or amendment.By metadata verification completion module according to the metadata of actual source database
Field information carries out verification and information completion to the field of Data Vault model, it is ensured that the unification of field.
Field data types adaptation module is used for the data type of the field of Data Vault model and metadatabase
The data type of field is adapted to, and in source database and not identical target database type, which may insure field
Data format is mutually unified, and field data types adaptation module includes type comparison module, type matching module and compatible lookup
Module, type comparison module is for the data type of the field of the more same Data Vault model and the field of metadatabase
Whether identical, type matching module is used for the field type of data type and source database in the field of Data Vault model
There are it is different when, in target data library lookup type identical with the data type of source database, if it is found, then by Data
The data type of the field of Vault model is revised as corresponding type, is searched if not finding using compatible searching module
The data type of the data type mutually compatible with the data type of the field of metadata and the field that Data Vault model is set
For type compatible accordingly.
Table module is built for according to the Data Vault model and model name mould after verification completion and type adaptation
The title of library, table and field that block exports generates the initialization statement of corresponding library and table, is by these initialization statements
The basic framework of data warehouse can be established, each table of active layer, model layer and application layer is such as pasted, such as hub table, link table
Sat table, pit table, bridge table etc..
Data extraction module is used for library, table and field according to Data Vault model and model name module output
Title, generate and export from source database extract data to data warehouse patch active layer sentence of isolating；Data loading module is used
In the title according to the library of Data Vault model and model name module output, table and field, generation and output will count
It is loaded into the loading sentence built in the table that table module is established according to from data warehouse patch active layer, data extraction module includes isolating
Tool, data loading module include data processing tools, isolate tool and data processing tools are distinguished in the form of plug-in unit
It is present in data extraction module and data loading module, isolates tool and data processing tools are all made of existing software
Or plug-in unit, they can be set it is multiple, to be deployed according to different needs.
Task analysis module be used for isolate sentence and load sentence analyze comprising dependence analysis module
With resource time consuming analysis module, dependence analysis module is used to analyze the relation of interdependence data between each sentence, money
Source time consuming analysis module be used for analyze each isolate sentence or load sentence the resource time-consuming data estimated.
Task scheduling modules are used for according to task dependence data and resource time-consuming data to sentence and the loading of isolating
The execution of sentence is scheduled, and task scheduling modules include scheduling tool, and so-called scheduling tool is the plug-in unit of a dispatching algorithm,
By replacing different scheduling tools, so that it may the dispatching algorithm for realizing different purposes, such as time shortest dispatching algorithm, expense
The smallest dispatching algorithm, dispatching algorithm least in power-consuming, the smallest dispatching algorithm of volume of transmitted data etc..Work is dispatched in the present embodiment
Tool includes calculating power prediction module and scheduling module, calculates power prediction module for the ID value according to machine each in system, prediction
The computing capability of machine, ID value is related to Machine Batch, and the batch of machine is newer, and the length of ID value is longer, calculates power prediction module
Module is estimated including ID acquisition module, calculation power and remaining power of calculating estimates module, and ID acquisition module is used to obtain all in system
The ID value of available machine and equipment, calculation power estimate module and are used to estimate its total computing capability according to the ID value of each equipment,
Residue calculates power and estimates module for the task current according to each machine, judges its remaining computing capability, scheduling module is used for
The dependence and resource time-consuming data of the remaining calculation power and each task estimated according to each machine carry out the allotment of task,
The allotment uses time shortest dispatching algorithm, since in actual task distribution and control process, all machines are all
Calling and operation are realized by ID value, therefore in the application, the length of ID value is combined with the batch of machine, and batch
Again it is related to machine performance, batch is newer, and machine performance is higher, thus the application woth no need to individually go again acquisition machine it is each
Item parameter, it is possible to reduce processing step accelerates task scheduling processing efficiency.
In the technical solution of the present embodiment, the definition of the Data Vault model to be established is inputted by mode input module
File, this definition file generally define some basic information of Data Vault model, as each field of standard scale is believed
Breath, the satellite informations such as renewal time, update personnel, then according to this definition file generated Data Vault model；Model name
Module generated and exported according to the Naming conventions of the Data Vault model specification each library under the Data Vault model, table with
And the title of field, it builds table module and then generates the initialization statement for creating corresponding table and library according to the title of generation；Data are taken out
Modulus block and data loading module generate isolate sentence and the loading sentence of data respectively；Task point is also set up in the present embodiment
Analysis module sentence and loads sentence and analyzes to above-mentioned isolate, by task scheduling modules based on the analysis results to each pumping
Number sentence and the execution sequence for loading sentence are scheduled with the time.Realize extraction, the data mart modeling, task schedule of data
Dynamicization etc. all multi-steps is handled, and related personnel only needs to be concerned about the service logic of core, does not need concern too much
Details is developed, the development cycle of global data warehouse is significantly reduced, reduces the staff size and cost of exploitation, is promoted
Automation, the intelligent level of global data warehouse exploitation and maintenance.
Isolate tool, output handling implement and scheduling tool be present in the form of plug-in unit in corresponding module, with
These tools are present in corresponding module by the form of plug-in unit, the form of this modular insert words can be convenient to these
Tool is replaced, and is handled using other algorithms, convenient for being expanded and being transformed to system, so that the versatility of system is more
By force.
The present invention also provides a kind of data warehouses intelligently to construct stowage, and the method use above-mentioned system, the party
Method the following steps are included:
Mode input step defines file generated Data Vault model according to input Data Vault model；
Completion step is verified, the metadata obtained according to the field information of Data Vault model and inquiry source database
Verification and information completion are carried out to the field of Data Vault model；
Model names step, according to the Naming conventions of Data Vault model, export library, table, field title；
Field data types adaptation step, by the field of the data type of the field of Data Vault model and metadatabase
Data type be adapted to；
Table step is built, according to the Data Vault model and model name module after metadata verification completion module completion
The title in the library of output, table and field generates the initialization statement of corresponding library and table；
Data pick-up step, according to the library of Data Vault model and model name module output, table and field
Title generates and exports the sentence of isolating for extracting data to data warehouse patch active layer from source database；
Data loading step, according to the library of Data Vault model and model name module output, table and field
Title is generated and is exported and data are pasted the loading sentence that active layer is loaded into the table for building the foundation of table module from data warehouse；
Task analysis step, to isolate sentence and load sentence analyze, obtain task dependence data and money
Source time-consuming data；
Task schedule step, according to task dependence data and resource time-consuming data to sentence and the loading sentence of isolating
Execution be scheduled.
The above are merely the embodiment of the present invention, the common sense such as well known specific structure and characteristic are not made excessively herein in scheme
Description, all common of technical field that the present invention belongs to before one skilled in the art know the applying date or priority date
Technological know-how can know the prior art all in the field, and have using routine experiment means before the date
Ability, one skilled in the art can improve in conjunction with self-ability under the enlightenment that the application provides and implement we
Case, some typical known features or known method should not become the barrier that one skilled in the art implement the application
Hinder.It should be pointed out that for those skilled in the art, without departing from the structure of the invention, if can also make
Dry modification and improvement, these also should be considered as protection scope of the present invention, these all will not influence the effect that the present invention is implemented and
Patent practicability.The scope of protection required by this application should be based on the content of the claims, the specific reality in specification
Applying the records such as mode can be used for explaining the content of claim.
Claims (7)
1. a kind of data warehouse intelligently constructs Load System, it is characterised in that: include:
Mode input module, the mode input module are used to input Data Vault model for user and define file and generate
Data Vault model；
Model names module, and model name module is used for the Naming conventions according to Data Vault model, output library, table,
The title of field；
Build table module, it is described build table module for according to the library of Data Vault model and model name module output, table with
And the title of field generates the initialization statement of corresponding library and table；
Data extraction module, for according to the library of Data Vault model and model name module output, table and field
Title generates and exports the sentence of isolating for extracting data to data warehouse patch active layer from source database；
Data loading module, for according to the library of Data Vault model and model name module output, table and field
Title is generated and is exported and data are pasted the loading sentence that active layer is loaded into the table for building the foundation of table module from data warehouse；
Task analysis module, the task analysis module be used for isolate sentence and load sentence analyze, obtain task
Dependence data and resource time-consuming data；
Task scheduling modules, the task scheduling modules are used for according to task dependence data and resource time-consuming data to isolating
Sentence and the execution for loading sentence are scheduled.
2. a kind of data warehouse according to claim 1 intelligently constructs Load System, it is characterised in that: further include metadata
Completion module is verified, the metadata verification completion module is used for field information and query source according to Data Vault model
The metadata that database obtains carries out verification and information completion to the field of Data Vault model.
3. a kind of data warehouse according to claim 1 intelligently constructs Load System, it is characterised in that: further include Field Count
According to type adaptation module, the field data types adaptation module be used for by the data type of the field of Data Vault model with
The data type of the field of metadatabase is adapted to.
4. a kind of data warehouse according to claim 1 intelligently constructs Load System, it is characterised in that: the data pick-up
Module includes tool of isolating, and the data loading module includes data processing tools, and the task scheduling modules include scheduling work
Tool, the tool of isolating, output handling implement and scheduling tool are present in corresponding module in the form of plug-in unit.
5. a kind of data warehouse according to claim 1 intelligently constructs Load System, it is characterised in that: further include configuration mould
Block, the configuration module is for configuring database essential information and configuration item.
6. a kind of data warehouse intelligently constructs stowage, it is characterised in that: method includes the following steps:
Mode input step defines file generated Data Vault model according to input Data Vault model；
Completion step is verified, the metadata pair obtained according to the field information of Data Vault model and inquiry source database
The field of Data Vault model carries out verification and information completion；
Model names step, according to the Naming conventions of Data Vault model, export library, table, field title；
Build table step, according to after metadata verification completion module completion Data Vault model and model name module output
Library, table and field title generate the initialization statement of corresponding library and table；
Data pick-up step, according to the library of Data Vault model and model name module output, the title of table and field,
It generates and exports the sentence of isolating for extracting data to data warehouse patch active layer from source database；
Data loading step, according to the library of Data Vault model and model name module output, the title of table and field,
It generates and exports and data are loaded into the loading sentence built in the table that table module is established from data warehouse patch active layer；
Task analysis step, to isolate sentence and load sentence analyze, obtain task dependence data and resource consumption
When data；
Task schedule step sentence and loads sentence and holds according to task dependence data and resource time-consuming data to isolating
Row is scheduled.
7. a kind of data warehouse according to claim 6 intelligently constructs stowage, it is characterised in that: in verification completion step
Suddenly with build between table step further include: field data types adaptation step, by the data type of the field of Data Vault model
It is adapted to the data type of the field of metadatabase.
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